Abstract
Crop insurance, though clearly needed, has not taken root in Kenyan agriculture, and what little exists is indemnity based, meaning that a farmer is compensated only based on assessed crop damage or harvest shortfall. This is often cumbersome and expensive for the average subsistence farmer. A better approach is to use index based insurance, whereby an agreed index is computed and the farmer is compensated or not compensated depending on its value. Remote sensing technology, which is now widely available globally, provides such an index, the Normalized Difference Vegetation Index (NDVI), which is an acknowledged indicator of crop health at different stages of crop growth. This paper reports on a study carried out in mid-2019 to investigate the possibility of applying remote sensing in this way to enable crop insurance for maize farmers in Migori County, Kenya. Sentinel 2 imagery from May 2017 (taken as the insurance year) was acquired, classified and NDVI generated over the study area. An 8 Km × 8 Km grid was overlaid and average NDVI computed per such grid cell. Similar imagery for May 2016 was acquired and similarly processed to provide reference NDVI averages. For any grid cell then, if Ap be the insurance year NDVI and Ar the reference NDVI, the insurance index was computed as (Ap - Ar), and farmer compensation would be triggered if this value was negative. Results show that out of about 85 small holder farms in the study area, 30 would have qualified for such compensations. These results are recommended for further refining and pilot testing in the study area and similar maize growing areas.
Highlights
IntroductionDrought is one of the risks to crops that affect millions of small holder farmers
This paper reports on a study carried out in mid-2019 to investigate the possibility of applying remote sensing in this way to enable crop insurance for maize farmers in Migori County, Kenya
Crop insurance in Kenya has been experienced since around 2006 [10], when there emerged considerable interest in agricultural insurance stimulated by growing interest among international agencies willing to partner with local insurance companies to develop such insurance in respect of crops and livestock
Summary
Drought is one of the risks to crops that affect millions of small holder farmers. In Migori County, small holder farmers have experienced the ravages of drought in all forms; from mild to severe, from severe to catastrophic and from short to long-term. Whenever a severe drought occurs, small holder farmers are left severely food insecure and often resort to government and Non-Governmental Organizations (NGOs) for food aid and other assistance. This paper argues that remote sensing offers viable solutions to offset crop losses in such circumstances. This argument is grounded further in the findings of Towery et al [1] who described the potential of aerial photography and remote sensing in crop hail damage assessment
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